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Author : Borus Martinus Johannes Petrus Jungbacker
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (255 download)
Download or read book On Importance Sampling for State Space Models written by Borus Martinus Johannes Petrus Jungbacker and published by . This book was released on 2005 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Siem Jan Koopman
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (13 download)
Download or read book Fast Efficient Importance Sampling by State Space Methods written by Siem Jan Koopman and published by . This book was released on 2014 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: We show that efficient importance sampling for nonlinear non-Gaussian state space models can be implemented by computationally efficient Kalman filter and smoothing methods. The result provides some new insights but it primarily leads to a simple and fast method for efficient importance sampling. A simulation study and empirical illustration provide some evidence of the computational gains.
Author : Hermann Singer
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (976 download)
Download or read book Langevin and Kalman Importance Sampling for Nonlinear Continuous-discrete State Space Models written by Hermann Singer and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Oliver Grothe
Publisher :
ISBN 13 :
Total Pages : 43 pages
Book Rating : 4.:/5 (13 download)
Download or read book The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models written by Oliver Grothe and published by . This book was released on 2017 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider Particle Gibbs (PG) as a tool for Bayesian analysis of non-linear non-Gaussian state-space models. PG is a Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the Gibbs procedure to update the latent and potentially high-dimensional state trajectories. We propose to combine PG with a generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially improve the mixing and the efficiency of the PG draws from the posterior of the states and the parameters relative to existing PG implementations.The efficiency gains achieved by PEIS are illustrated in PG applications to a univariate stochastic volatility model for asset returns, a Gaussian nonlinear local-level model for interest rates, and a multivariate stochastic volatility model for the realized covariance matrix of asset returns.
Author : The late James Durbin
Publisher : OUP Oxford
ISBN 13 : 019964117X
Total Pages : 368 pages
Book Rating : 4.1/5 (996 download)
Download or read book Time Series Analysis by State Space Methods written by The late James Durbin and published by OUP Oxford. This book was released on 2012-05-03 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.
Author : Yong Zeng
Publisher : Springer Science & Business Media
ISBN 13 : 1461477891
Total Pages : 358 pages
Book Rating : 4.4/5 (614 download)
Download or read book State-Space Models written by Yong Zeng and published by Springer Science & Business Media. This book was released on 2013-08-15 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.
Author : Kai Ming Lee
Publisher : Rozenberg Publishers
ISBN 13 : 9036101697
Total Pages : 150 pages
Book Rating : 4.0/5 (361 download)
Download or read book Filtering None-Linear State Space Models. Methods and Economic Applications written by Kai Ming Lee and published by Rozenberg Publishers. This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Siem Jan Koopman
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (837 download)
Download or read book Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models written by Siem Jan Koopman and published by . This book was released on 2011 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michael Vidne
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (867 download)
Download or read book State-Space Models and Latent Processes in the Statistical Analysis of Neural Data written by Michael Vidne and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the fourth chapter we develop a more general approach to the state-space filtering problem. Our method solves the same recursive set of Markovian filter equations as the particle filter, but we replace all importance sampling steps with a more general Markov chain Monte Carlo (MCMC) step. Our algorithm is especially well suited for problems where the model parameters might be misspecified.
Author : James Durbin
Publisher : Oxford University Press
ISBN 13 : 9780198523543
Total Pages : 280 pages
Book Rating : 4.5/5 (235 download)
Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by Oxford University Press. This book was released on 2001-06-21 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space time series analysis emerged in the 1960s in engineering, but its applications have spread to other fields. Durbin (statistics, London School of Economics and Political Science) and Koopman (econometrics, Free U., Amsterdam) extol the virtues of such models over the main analytical system currently used for time series data, Box-Jenkins' ARIMA. What distinguishes state space time models is that they separately model components such as trend, seasonal, regression elements and disturbance terms. Part I focuses on traditional and new techniques based on the linear Gaussian model. Part II presents new material extending the state space model to non-Gaussian observations. c. Book News Inc.
Author : Julien Cornebise
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.:/5 (251 download)
Download or read book Adaptive Methods for Sequential Importance Sampling with Application to State Space Models written by Julien Cornebise and published by . This book was released on 2008 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Siem-Jan Koopman
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (713 download)
Download or read book Numerically Accellerated Importance Sampling for Nonlinear Non-Gaussian State Space Models written by Siem-Jan Koopman and published by . This book was released on 2011 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Arnaud Doucet
Publisher : Springer Science & Business Media
ISBN 13 : 1475734379
Total Pages : 590 pages
Book Rating : 4.4/5 (757 download)
Download or read book Sequential Monte Carlo Methods in Practice written by Arnaud Doucet and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.
Author : Hermann Singer
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (965 download)
Download or read book Simulated Maximum Likelihood for Continuous-discrete State Space Models Using Langevin Importance Sampling written by Hermann Singer and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sascha Mergner
Publisher : Universitätsverlag Göttingen
ISBN 13 : 3941875221
Total Pages : 235 pages
Book Rating : 4.9/5 (418 download)
Download or read book Applications of State Space Models in Finance written by Sascha Mergner and published by Universitätsverlag Göttingen. This book was released on 2009 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the context of widely used concepts in finance. The presented material will be useful for financial economists and practitioners who are interested in taking time-variation in the relationship between financial assets and key economic factors explicitly into account. The empirical part illustrates the application of the various methods under consideration. As a distinctive feature, it includes a comprehensive analysis of the ability of time-varying coefficient models to estimate and predict the conditional nature of systematic risks for European industry portfolios.
Author : Christian Robert
Publisher : Springer Science & Business Media
ISBN 13 : 1441915753
Total Pages : 297 pages
Book Rating : 4.4/5 (419 download)
Download or read book Introducing Monte Carlo Methods with R written by Christian Robert and published by Springer Science & Business Media. This book was released on 2010 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Author : James Durbin
Publisher : Cambridge University Press
ISBN 13 : 9780521835954
Total Pages : 398 pages
Book Rating : 4.8/5 (359 download)
Download or read book State Space and Unobserved Component Models written by James Durbin and published by Cambridge University Press. This book was released on 2004-06-10 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of developments in the theory and application of state space modeling, first published in 2004.
